Model Selection Information Criteria for Non-Nested Latent Class Models

Ting Hsiang Lin and C. Mitchell Dayton

Journal of Educational and Behavioral Statistics, 1997, vol. 22, issue 3, 249-264

Abstract: Latent class models have been developed for assessment of hierarchic relations in scaling and behavioral analysis. This article investigated the use of three model selection information criteria—Akaike AIC, Schwarz SIC, and Bozdogan CAIC—for non-nested models. In general, SIC and CAIC were superior to AIC for relatively simple models, whereas AIC was superior for more complex models, although accuracy was often quite low for such models. In addition, some effects were detected for error rates in the models.

Keywords: latent class analysis; model selection criteria (search for similar items in EconPapers)
Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:22:y:1997:i:3:p:249-264

DOI: 10.3102/10769986022003249

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